The richness and complexity of the molecular regulatory network governing cell proliferation requires a concise and unambiguous method of representation. It is becoming difficult or impossible to keep in mind all of the molecular interactions that may be pertinent to the planning and interpretation of experiments in a given area or to generating functional hypotheses. Difficulties arise especially because of the rich cross-connectivity among different signaling pathways that control cell proliferation and DNA repair. In order to utilize extant information optimally, a road map of the known or suspected molecular interactions would be useful, if not essential. Not only must the information itself be handy, but literature citations for the pertinent evidence must be readily accessible. Moreover, the molecular interaction maps must be in a form that allows frequent updating to accommodate corrections and new data. Molecular interaction maps must be able to cope with the complexities that extensive experimental work has revealed. A diagram convention was therefore devised that allows protein-protein interactions and protein modification states to be clearly represented and that can cope with highly complex systems. The Molecular Interaction Map conventions were originally set forth in Kohn 1999 Mol. Biol. Cell 10: 2703-34, where the procedure was used in a comprehensive description of the G1/S mammalian cell cycle control network. Also included were an annotation list for the interactions depicted and reference citations. The map was placed on John Weinstein's web site (http://discover.nci.nih.gov). The monomolecular species are listed in an alphabetical index which gives the map coordinates where each species can be found. Multimolecular species are depicted by means of a convention of arrowed lines that connect the monomolecular components. Another convention is used to depict the complexities of protein modifications, especially phosphorylations. Symbol conventions also are defined for enzymatic action, stimulation, and inhibition. Each interaction is marked with a symbol that refers to an annotation list where salient facts and literature references can be found. The mapping conventions were formalized and extended to accommodate intramolecular controls, gene regulation, and events at the plasma membrane involving receptors, phosphoinositides, kinases, etc. This work was completed early during the current year, and was published, together with several example maps to illustrate different types of molecular interaction networks, in an American Institute of Physics journal (Kohn 2001 CHAOS 11: 84-97). During the rest of the current year, the main focus was the molecular interaction network that controls apoptosis in mammalian cells. Apoptosis regulates cell number of normal proliferative cell populations, such as prostatic glandular epithelial cells. Triggering of apoptosis in cancer cells is a major factor in the therapeutic action of cytotoxic drugs. Apoptosis is also a major factor in hormonal therapy, particularly in breast and prostate tumors. Cancer cells however often loose competence for apoptosis, thus contributing to drug resistance. Targeting of key steps in the apoptosis control machinery by means of drugs or hormonal agents is a promising route to improved therapy, but requires understanding the molecular details, as well as the overall logic, of the apoptosis control machinery. Relevant information at the molecular level continues to be published at an accelerating pace. However, organizing this complex information in a functionally revealing manner is difficult, as well as urgent. The molecular interaction maps that we have prepared suggest that the core components of the apoptosis network can be viewed as modular. This greatly facilitates both the preparation and the understanding of the network diagrams, because relatively few inputs and outputs communicate with the molecular complexities within a module. Global diagrams of the logical interconnections between modules therefore need not include the complexities of what is going on within each module, and one can zoom in to reveal these details when necessary. In collaboration with John Weinstein's group in our Laboratory, together with several other collaborating laboratories, we investigated the differences in gene expression profiles between a parental and a drug-resistant human prostate cell line. The resistant line was found to have a profound defect in apoptotic responses relative to the parental line. Gene expression profiles indicated a disproportionately elevated number of alterations of genes implicated in apoptosis. The molecular interaction maps are helping to formulate hypotheses on the cause of the apoptosis resistance and can help to design tests of these hypotheses. Future efforts will integrate this information with current published work from other laboratories studying apoptosis resistance in prostate cancer cells. We also plan to increase the gene profile coverage by moving from the current 1694-gene oncochip to arrays encompassing about 60,000 genes.